We adopt accuracy to evaluate the performance of node classification task. As for fairness metric, we adopt two quantitative group fairness metrics to measure the prediction bias. According to works [1]}, [2]}, we adopt demographic parity \(\Delta _{DP}=|\mathbb {P}(\hat{y}=1|s=-1)-\mathbb {P}(\hat{y}=1|s=1)|\)  and equal opportunity \(\Delta _{DP}=|\mathbb {P}(\hat{y}=1|s=-1, y=1)-\mathbb {P}(\hat{y}=1|s=1, y=1)|\) , where \(y\)  and \(\hat{y}\)  represent the ground-truth label and predicted label, respectively.
